code: def test_pixelwise_softmax(backend_default):
      inputs = np.array([0, 1, 3, 1, 2, -2]).reshape((2, 3))
      outputs = (
          1.0 / np.sum(np.exp(inputs - np.max(inputs, axis=0)), axis=0)
      ) * np.exp(inputs - np.max(inputs, axis=0))
      inputs = inputs.reshape((1, -1))
      outputs = outputs.reshape((1, -1))
      compare_tensors(
          PixelwiseSoftmax(c=2), inputs, outputs, deriv=False, tol=1e-6
      )
  
imports: from math import tanh
  import numpy
  from neon import NervanaObject
  from neon.transforms import Identity, Rectlin, Softmax, Tanh, Logistic, Sign, PixelwiseSoftmax
  from utils import allclose_with_out
label_desc: Use image node_id 19 for calling a global function with example usage: test_pixelwise_softmax(backend_default) without return types